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As a Manager within the Chief Control Office, you&#39;ll strategically enhance the bank&#39;s risk and control environment.</p>\n<p>You&#39;ll oversee, advise, and govern control activities supporting the effective management of both financial and non-financial risks, ensuring our frameworks, policies, and procedures are robust, compliant, and consistently implemented.</p>\n<p>Collaborating with risk, business, and infrastructure teams you will drive technical improvements, embed best practices, and deliver sustainable risk appropriate, control outcomes across the organisation.</p>\n<p>As our Manager, Strategy and Enablement, Chief Control Office, you will:</p>\n<ul>\n<li>Own and provide advisory support for risk and control management processes, ensuring alignment with internal risk frameworks and regulatory requirements</li>\n</ul>\n<ul>\n<li>Oversee key assessments and reviews to ensure the effectiveness of financial and non-financial risk controls, supporting risk appetite and long-term objective</li>\n</ul>\n<ul>\n<li>Act as a senior escalation point for risk and control matters, advising executive leadership and influencing decision-making</li>\n</ul>\n<ul>\n<li>Analyze and assess the risk and control environment, ensuring organisational readiness and implementing robust mitigation strategies</li>\n</ul>\n<ul>\n<li>Support key papers, and governance forums, to reinforce risk culture, embed risk management framework principles, and drive continuous improvement</li>\n</ul>\n<ul>\n<li>Deliver insightful management information (MI) and risk reports to senior stakeholders, enabling informed and appropriate risk-based decisions</li>\n</ul>\n<ul>\n<li>Build and maintain strong relationships with risk, control, business, and infrastructure teams, promoting a culture of collaboration, accountability, and risk awareness</li>\n</ul>\n<p>You&#39;ll likely have the following qualifications to succeed in this role:</p>\n<ul>\n<li>Demonstrates a proactive, analytical approach to identifying challenges, taking ownership of solutions, and driving initiatives to successful resolution</li>\n</ul>\n<ul>\n<li>Extensive experience in risk and control management, with deep knowledge of financial and non-financial risk frameworks (e.g., operational risk, conduct risk, compliance, credit, market risk)</li>\n</ul>\n<ul>\n<li>Proven track record of navigating complex control environments within a highly regulated environment</li>\n</ul>\n<ul>\n<li>Exceptional stakeholder management and collaboration abilities both internal and external to the team</li>\n</ul>\n<ul>\n<li>Confident and inclusive communicator, able to present clear data-driven insights and recommendations to executive and senior audiences</li>\n</ul>\n<ul>\n<li>Advanced analytical skills with expertise in Excel; familiarity with ServiceNow, Qliksense, and Performance Analytics is advantageous</li>\n</ul>\n<ul>\n<li>Experience with or interest in Gen AI applications for risk and control process improvement is advantageous</li>\n</ul>\n<ul>\n<li>Experience with both financial and non-financial risks and controls related to Finance teams</li>\n</ul>\n<p>As an HSBC employee, you will have access to tailored professional development opportunities to ensure you have the right skills for today and tomorrow. We offer a competitive pay and benefits package including a robust Wellness Hub, all in a welcoming and inclusive work environment. You will be empowered to drive HSBC&#39;s engagement with the communities we serve through an industry-leading volunteerism policy, a generous matching gift program, and a comprehensive program of immersive Sustainability and Climate Change Initiatives. 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In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.</p>\n<p>To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.</p>\n<p>The base salary range for this position is: $185,800-$260,100 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_467be5c4-940","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/7131932","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$185,800-$260,100 USD","x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs","Spark","Kafka","Ray","Airflow","BigQuery","Redis"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments","Feature engineering","Model optimization","Production monitoring","LLM/Gen AI techniques"],"datePosted":"2026-04-18T15:57:49.850Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments, Feature engineering, Model optimization, Production monitoring, LLM/Gen AI techniques","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":185800,"maxValue":260100,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_24be2797-0df"},"title":"HRBP, Operations","description":"<p>At Scale, we&#39;re seeking an HR Business Partner to partner with our Gen AI Operations team. As the HR Business Partner, Operations, you will be deeply embedded within the Gen AI Operations team, advising team members as our business scales, and supporting leaders in all people-related matters.</p>\n<p>You will provide end-to-end HRBP support across our growing and evolving Gen AI business unit, including directly driving org health initiatives, influencing org structure to effectively scale the team, and developing and implementing creative solutions as the team navigates new markets.</p>\n<p>Establish yourself as a trusted advisor and a knowledgeable, reliable, and empathetic partner for our employees and leaders across the Enterprise team.</p>\n<p>Coach and advise leaders on best people practices and uplevel manager skill sets.</p>\n<p>Lead project management for all people programs for the Enterprise organization, including org planning, onboarding, performance cycles, engagement surveys, and career development efforts.</p>\n<p>Drive organization and order for people data and use it to provide insights and recommendations to leaders.</p>\n<p>Work in a hybrid work environment (3 days/week) at our San Francisco Headquarters or New York office.</p>\n<p>Ideal candidates will have 5+ years of experience working in HR with progression and growth in scope, with 3+ years of experience in an HR Business Partner role at a fast-paced, high-growth company.</p>\n<p>Demonstrated experience engaging with executive-level leadership on org-wide initiatives, and ability to partner and build relationships with senior leadership.</p>\n<p>Strong ability to relate to, empathize with, and quickly build trust with people from diverse backgrounds.</p>\n<p>Proven ability to thrive in a fast-paced, iterative environment and embrace changes in focus and direction as needed.</p>\n<p>A passion for building scalable processes in a creative, thoughtful, and organized way.</p>\n<p>Experience supporting a global workforce across various job functions.</p>\n<p>Nice to haves: Strong knowledge of Google Sheets/Excel and demonstrated ability to influence decisions with data.</p>\n<p>Experience in Consulting or in an Operations and Strategy role at a fast-paced company.</p>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.</p>\n<p>Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant.</p>\n<p>You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. 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Architecture: Cloud Native Architecture in CSPs such as AWS, Azure, and GCP, Serverless Architecture</li>\n</ul>\n<ul>\n<li>Security: Platform security, Network security, Data Security, Gen AI &amp; Model Security, Encryption, Vulnerability Management, Compliance</li>\n</ul>\n<ul>\n<li>Networking: Architecture design, implementation, and performance</li>\n</ul>\n<ul>\n<li>Identify management: Provisioning, SCIM, OAuth, SAML, Federation</li>\n</ul>\n<ul>\n<li>Platform Administration: High availability and disaster recovery, cluster management, observability, logging, monitoring, audit, cost management</li>\n</ul>\n<ul>\n<li>Infrastructure Automation and InfraOps with IaC tools like Terraform</li>\n</ul>\n<ul>\n<li>Maintain and extend the Databricks environment to adapt to evolving complex needs.</li>\n</ul>\n<ul>\n<li>Deep Specialty Expertise in at least one of the following areas:</li>\n</ul>\n<ul>\n<li>Security - understanding how to secure data platforms and manage identities</li>\n</ul>\n<ul>\n<li>Complex deployments</li>\n</ul>\n<ul>\n<li>Public Cloud experience - experience designing data platforms on cloud infrastructure and services, such as AWS, Azure, or GCP, using best practices in cloud security and networking.</li>\n</ul>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience.</li>\n</ul>\n<ul>\n<li>Hands-on experience with Python, Java, or Scala, and proficiency in SQL, and Terraform experience are desirable.</li>\n</ul>\n<ul>\n<li>2 years of professional experience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and architectures</li>\n</ul>\n<ul>\n<li>2 years of customer-facing experience in a pre-sales or post-sales role</li>\n</ul>\n<ul>\n<li>Can meet expectations for technical training and role-specific outcomes within 6 months of hire</li>\n</ul>\n<ul>\n<li>This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed.</li>\n</ul>\n<p>Pay Range Transparency:</p>\n<p>Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. 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As a key member of our team, you will design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems, intelligent advertising systems, and large-scale machine learning pipelines.</p>\n<p>Our team is responsible for building systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You will work on high-impact systems that improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.</p>\n<p>As a Senior Machine Learning Engineer, you will:</p>\n<ul>\n<li>Design, build, and deploy production-grade machine learning models and systems at scale</li>\n<li>Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring</li>\n<li>Build scalable data and model pipelines with strong reliability, observability, and automated retraining</li>\n<li>Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems</li>\n<li>Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions</li>\n<li>Improve system performance across latency, throughput, and model quality metrics</li>\n<li>Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph &amp; transformers based, and LLM evaluation/alignment</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>3-5+ years of experience building, deploying, and operating machine learning systems in production</li>\n<li>Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals</li>\n<li>ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)</li>\n<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>\n<li>Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure</li>\n<li>Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions</li>\n<li>Experience improving measurable metrics through applied machine learning</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems</li>\n<li>Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)</li>\n<li>Experience working with real-time systems and low-latency production environments</li>\n<li>Background in feature engineering, model optimization, and production monitoring</li>\n<li>Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale</li>\n<li>Advanced degree in Computer Science, Machine Learning, or related quantitative field</li>\n</ul>\n<p>Potential Teams:</p>\n<ul>\n<li>Ads Measurement Modeling</li>\n<li>Ads Targeting and Retrieval</li>\n<li>Advertiser Optimization</li>\n<li>Ads Marketplace Quality</li>\n<li>Ads Creative Effectiveness</li>\n<li>Ads Foundational Representations</li>\n<li>Ads Content Understanding</li>\n<li>Ads Ranking</li>\n<li>Feed Relevance</li>\n<li>Search and Answers Relevance</li>\n<li>ML Understanding</li>\n<li>Notifications Relevance</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive Healthcare Benefits and Income Replacement Programs</li>\n<li>401k with Employer Match</li>\n<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>\n<li>Family Planning Support</li>\n<li>Gender-Affirming Care</li>\n<li>Mental Health &amp; Coaching Benefits</li>\n<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>\n<li>Generous Paid Parental Leave</li>\n</ul>\n<p>Pay Transparency:</p>\n<p>This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is $216,700-$303,400 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fc38e24f-97e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/6960831","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,700-$303,400 USD","x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs","Spark","Kafka","Ray","Airflow","BigQuery","Redis"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments","Feature engineering","Model optimization","Production monitoring","LLM/Gen AI techniques","LLM evaluation","Alignment","Fine-tuning","Knowledge distillation","RAG/agentic systems"],"datePosted":"2026-04-18T15:45:58.533Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments, Feature engineering, Model optimization, Production monitoring, LLM/Gen AI techniques, LLM evaluation, Alignment, Fine-tuning, Knowledge distillation, RAG/agentic systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216700,"maxValue":303400,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_071153a3-427"},"title":"Delivery Partner Manager, Services","description":"<p>At Databricks, we are seeking a Delivery Partner Manager, Services to join our Professional Services team. 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You will focus on one of three high-impact tracks:</p>\n<p><strong>Track 1: AI Platform Projects</strong></p>\n<ul>\n<li>Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox.</li>\n<li>Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.</li>\n<li>Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable.</li>\n</ul>\n<p><strong>Track 2: Distributed Inference &amp; Systems Optimization</strong></p>\n<ul>\n<li>Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.</li>\n<li>Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.</li>\n</ul>\n<p><strong>Track 3: Information Retrieval &amp; RAG for Gen AI</strong></p>\n<ul>\n<li>Lead the design and development of Retrieval-Augmented Generation (RAG) systems.</li>\n<li>Build and maintain core information retrieval infrastructure—vector databases and knowledge graphs—to enable accurate grounding of Gen AI models.</li>\n<li>Ship language models and 3D objects as a service for the Roblox community, making creation easier.</li>\n</ul>\n<p><strong>You Have</strong></p>\n<ul>\n<li>Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.</li>\n<li>Experience with high performance distributed systems, ML Infrastructure, LLM fine tuning/RL, Information Retrieval and Gen AI context generation.</li>\n<li>Expertise in one or more of the following key areas:</li>\n<li>AI/ML Platform Data stores - Features stores, Vector DBs and Knowledge Graphs.</li>\n<li>LLMs - Fine tuning, Safety.</li>\n<li>Agentic systems - Agent evaluation, context engineering.</li>\n</ul>\n<ul>\n<li>Experience building agentic applications with context for real world applications.</li>\n<li>Collaborative mindset and experience integrating and deploying optimized models with cross-functional teams, including data scientists and software engineers.</li>\n<li>Experience with graph databases and large-scale GNNs (Graph Neural Networks)</li>\n<li>Experience working with Kubernetes</li>\n<li>Experience working with one or more cloud providers (e.g., AWS, Azure, GCP)</li>\n<li>Experience working with high availability systems</li>\n<li>Experience working with ML models, LLMs or other AI systems</li>\n</ul>\n<p>You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.</p>\n<p>As you apply, you can find more information about our process by signing up for Speak\\_. You&#39;ll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.</p>\n<p>For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. 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